A methodology for transparent knowledge specification in a dynamic tuning environment

The increasing use of parallel/distributed applications demands a continuous support to take significant advantages from parallel power. This includes the evolution of performance analysis and tuning tools which automatically allows for obtaining a better behavior of the applications. Different approaches and tools have been proposed and they are continuously evolving to cover the requirements and expectations of users. One such tool is MATE (Monitoring Analysis and Tuning Environment), which provides automatic and dynamic tuning for parallel/distributed applications. The knowledge used by MATE to analyze and take decisions is based on performance models which include a set of performance parameters and a set of mathematical expressions modeling the solution of the performance problem. These elements are used by the tuning environment to conduct the monitoring and analysis steps, respectively. The tuning phase depends on the results of the performance analysis. This paper presents a methodology to specify performance models. Each performance model specification can be automatically and transparently translated into a piece of software code encapsulating the knowledge to be straightforwardly included in MATE. Applying this methodology, the user does not have to be involved in the implementation details of MATE, which makes the usage of the tool more transparent.Fil: Caymes Scutari, Paola Guadalupe. Universidad Tecnológica Nacional. Facultad Regional de Mendoza; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; ArgentinaFil: Morajko, A.. Universitat Autònoma de Barcelona; EspañaFil: Margalef, T.. Universitat Autònoma de Barcelona; EspañaFil: Luque, E.. Universitat Autònoma de Barcelona; Españ

Performance Analysis of Shared-Memory Parallel Applications Using Performance Properties

Tuning parallel code can be a time-consuming and difficult task. We present our approach to automate the performance analysis of OpenMP applications that is based on the notion of performance properties. Properties are formally specified in the APART specification language (ASL) with respect to a specific data model. We describe a data model for summary (profiling) data of OpenMP applications and present performance properties based on this data model. We evaluate the usability of the properties on several example codes using our OpenMP profiler ompP to acquire the profiling data